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Category: Economists on Economics

Neoclassical Finance and Reality (3 lectures by Robert Shiller)

Neoclassical Finance and Reality (3 lectures by Robert Shiller)

Neoclassical Finance and Reality by Robert Shiller (Yale) @ Princeton (October 8-10, 2013).

The third lecture (ppt) gives a good idea about the forthcoming book by George A. Akerlof & Robert J. Shiller: Phishing for Phools: The Economics of Manipulation and Deception (Amazon)




David Levine has an interesting article on neuroeconomics (entitled Neuroeconomics?). While skimming through the article I found an interesting analogy concerning neuroeconomics.I did not yet read the article (will do that soon).  Nevertheless, here are some remarks concerning the analogy.

David Levine argues:

“Suppose you wanted to study Microsoft Word in order, say, to build a better word processor. Would you study the CPU of a PC? Would you  study  how  the  RAM  is  wired?  Or  the  ASICS?  Would  you  study  the  binary  code? Surely you would do none of those things. Would you study the source code? Probably not even that, most likely you would use the program, observe how it worked, and figure out  how  to  build  a  program  that  did  the  same  thing.  That  is  what  economists  do.  We observe  human  behavior  and  figure  out  models  that  behave  the  “way  humans  do.”  We have no reason to believe that better understanding the wiring of the brain would improve our models any more than understanding the micro-code on an x86 chip would improve lead to improvements in word processors.” (Source)

I am not a computer scientist, yet this sounds like a bad analogy.

Concerning software (e.g., a word processor) the answer to Levine’s question is, it depends. First you need to ask whether the particular software you have is dependent on the platform it operates, or not. There are certainly a lot of platform independent software. But some software will not work if you move it to another computer — say from a Linux based system to a Windows based system, or from a 64bit system to a 32bit system. Sometimes, in order to understand how a software works and how you may improve it, you need to understand the operating system and the architecture of the processor. But this is not where the analogy fails.

Analogy fails, because it bypasses at least two arguments for neuroeconomics. Firstly, neuroeconomics shows that economic behavior may be context-dependent. Hence, explaining particular economic phenomena may require an understanding how context influences economic behavior. And in order to develop a good model of context dependent economic behavior it may be useful to understand how brain “produces” economic behavior under different conditions. If your word processor behaves differently when it is simultaneously running a Matlab code in the background, it may be good idea to inquire and understand how Matlab and Word interacts at a lower level (e.g., at the level of the operating system, chipset, processor). Secondly, even if neural level correlates of economic behavior is well in line with the assumptions of economic theory, a better understanding of how brain works in relation to economic behavior may improve our understanding of economic phenomena. Here is the analogy for this. Let us assume that there are two coders John and Mike. John only knows a couple of platform independent programing languages. He has no understanding of operating systems and computer architecture. Nevertheless, thanks to platform independent programing languages, he produces functional software for the Java platform or for Adobe Air. Mike, on the other hand, knows how a computer works, how platform independent programing languages interact with the operating system and how processors react to commands coming from the operating system. Mike, too, writes functional software for Java and Adobe Air. In terms of what they do John and Mike are equivalent. However, in terms of their understanding of what they do they are not. Mike knows better. His understanding of how software works is superior to that John. Economists who ignore neuroeconomics is like John. They produce functional models of economic behavior. However, if they would like to have a better understanding of economic behavior, they are well advised to learn more about how lower levels work by reading (and not ignoring)neuroeconomics. Remember, Levine argues:

“We have no reason to believe that better understanding the wiring of the brain would improve our models any more than understanding the micro-code on an x86 chip would improve lead to improvements in word processors.”

Well, this is partly true. If we know that our economic models are correct, understanding the neural-level will not improve our models. But even if our models are correct, a better understanding of neural correlates of economic behavior will improve our understanding of economic phenomena. Also note that we do not know whether all of our economic models are correct or not. Thus, neuroeconomics may also help us develop better models of economic behavior.

As I have said, I am not a computer scientist. So, probably I have made many mistakes in my software-hardware analogies. My computer-analogy free argument concerning how neuroeconomics may be useful for economists is here: Neuroeconomics: more than inspiration, less than revolution, Journal of Economic Methodology, 2010, 17(2): 159-169.

Interesting discussion: 5 themes for Serious Economics!

Interesting discussion: 5 themes for Serious Economics!

Here is what interests me at the moment: the cluster of related models! Right now I am working on a paper (with Petri Ylikoski) which deals with the clustered nature of models in economics. (Our point concerns the philosophy of models.) So I’ll just note (for myself) the comments that relates to this issue.

Bruce Edmonds says:

“5. Recognising the need for clusters of related models of many kinds and levels. Following on from the last point, we are faced with a dilemma – complex models that relate more directly to what is observed but are hard to understand and analyse (i.e. relevance); or simpler models that dont relate to observations (at best to our ideas about what we observe) but that can Social phenomena are not only complex but that can be thoroughly understood (i.e. rigour). The truth is we need both rigour and relevance, which means we will not achieve this using one model or one technique. Rather we will have to make do with “clusters” of related models capturing the phenomena – different aspects, at different granularities, and at different levels of abstration. So, for example, we might acquire a series of representations of evidence from many different sources (ethnographic, statistical, social network, interviews, observations, lab experiments etc.), theser might be related to complex “data integration” simulation models that are consistent with as many of these as possible. Then this complex simulation might be a safe target for simplification and abstraction in other, simulation and alaytic models, since these can be adequately tested for relevance against the simulation model they are about.” Bruce Edmonds

Geoff Davies comments:

” “Clusters of related models”. Yes, you can’t hope, at the beginning, to make a model that includes everything that might be relevant. Even if you did, you wouldn’t understand its behaviour any better than you understand the real world. You have to start with simplified models that are not only tractable (with or without computers) but whose behaviour you can understand. This is true even though we know we’re dealing with a system that has emergent properties, and so you can’t use a simple reductionist approach. An example of a good approach I think is Steve Keen’s macro modelling of Minsky’s financial instability hypothesis. He has been progressively adding factors, and looking at the resulting (nonlinear, sometimes counter-intuitive) behaviour to see if it captures anything of the qualities of real world behaviour. (See, for example, . That’s all right Steve, you can scratch my back sometime.)

As you accumulate simplified models of various phenomena, you have to worry if they’re compatible. In my field, geophysicists and geochemists came to quite different pictures of Earth’s mantle, one layered, the other not. Such incompatibilities tell you there’s something important you (collectively) don’t understand. It has taken about three decades to begin to bring the two disciplines into compatibility, and the arguing is far from over.” Geoff Davies

Notes on Economics and the Future of Quantitative Social Science

Notes on Economics and the Future of Quantitative Social Science

Notes on Economics and the Future of Quantitative Social Science

Andrew J. Oswald (University of Warwick)

This brief paper is written for a meeting in Cambridge-Mass in May 2010. It offers speculations on the scientific future of economics (and some of the quantitative parts of social science). It is closer to guesswork than science and is not designed to be a careful, full study. As an aid to anyone interested in possible trends, it provides data on the most-referenced journal articles in modern economics.
Read the full article here (pdf)

HT: Tyler Cowen

Catch 22 for History of Economic Thought

Catch 22 for History of Economic Thought

Here is Doug Mackenzie’s formulation of Catch 22 for HET at the SHOE list:

“That is a catch 22: they must believe that HET leads to pubs in top
journals, but top journals will not bother with HET unless most
economists see it as important. Of course, HOPE and JHET are good
hits for any economist, so long as they have hits in mainstream
journals, but HET is at best optional for most economists. Another
avenue is teaching, its pretty common for mainstream economists to
babble about how Arrow and Debreu formalized Smith’s conjecture or
how Keynes converted everyone in the universe to his view in less
that ten minutes, and they look foolish to anyone who knows HET.
Trouble is that they mostly preach this nonsense to those who know no
better, so there is no embarrassment factor. How then can the
foolishness of knowing virtually nothing about the history of ones
own alleged area of expertise be made apparent? How can we make the
feel as foolish as they are?” (Source)

I especially like the second part.

This was a response to a post which was reporting that at least three distinguished professional economists (full professors) did not know about Frank Knight. You are advised to read the entire tread.

How Did Economists Get It So Wrong? Replies to Krugman and more

How Did Economists Get It So Wrong? Replies to Krugman and more

You already know Krugman’s “How Did Economists Get It So Wrong?“. You may want to read the following:

Also see: Barry Eichengreen’s piece.

Thanks to Greg Mankiw and Ceyhun Elgin for the pointers.

How Did Economists Get It So Wrong?

How Did Economists Get It So Wrong?

Foto: Wikimedia Commons, Dosya: 800px-Financialcrisisconsumerspendings.JPG
Photo source: Wikimedia Commons, File: 800px-Financialcrisisconsumerspendings.JPG

“[…] the economics profession went astray because economists, as a group, mistook beauty, clad in impressive-looking mathematics, for truth. […] When it comes to the all-too-human problem of recessions and depressions, economists need to abandon the neat but wrong solution of assuming that everyone is rational and markets work perfectly. The vision that emerges as the profession rethinks its foundations may not be all that clear; it certainly won’t be neat; but we can hope that it will have the virtue of being at least partly right. “

These are Paul Krugman’s words. You may read the full article here.

The question is the following: Will philosophers of economics come to the rescue?

State of Economics after the Crisis

State of Economics after the Crisis

Source: Wikimedia Commons, File:2007-2009_World_Financial_Crisis.svg


Earlier I mentioned The Economist articles concerning the state of economics after the crisis. Here is a small reading list for the interested philosopher of economics:

The Economist take:

Some interesting blog posts concerning the issue:

Books that you may consider reading:

  • Foster, John Bellamy & Fred Magdoff (2009) The Great Financial Crisis, Monthly Review
  • Wessel, David (2009) In Fed We Trust: Ben Bernanke’s War on the Great Panic, Crown Business.

Articles that you may consider reading:

What went wrong with economics

What went wrong with economics

economistThe philosophy of economics makes it to the cover of The Economist!

July 18th (2009) issue of The Economist asks: “What went wrong with economics?”

Philosophers of economists (who did not make it to the cover) may be interested in reading The Economists’ take on the current state of economics in the light of the crisis.

Here are the articles in the July 18th issue:

* What went wrong with economics? And how the discipline should change to avoid the mistakes of the past

* The state of economics: The other-worldly philosophers

* Financial economics: Efficiency and beyond

Thanks to Alessandro (Lanteri) for bringing this to our attention.